The document discusses NASA's efforts to create a knowledge graph to map workforce skills. It explains that NASA is asking questions like what are the current workforce skill sets, how skills can be grouped, and how individuals can identify new skills or careers. The document outlines NASA's process for developing the knowledge graph which includes understanding the domain, defining a model, gathering data from sources like O*NET, and analyzing the data to create graphs that can compare occupations and recommend career changes or training. The knowledge graph is intended to help with workforce planning, identifying expertise, and outlining career paths.

1. National Aeronautics and Space Administration
www.nasa.gov
Identifying Workforce Skills
& Capabilities Knowledge
Graph
David Meza
Sr. Data Scientist
Office of the Chief Human Capital Officer
1

2. Creating Knowledge Graphs
• Understand the Domain
• Ask the Questions
• Define your Model
• Do the Analysis
2

3. 3
Understand Your Domain

4. 4

5. HR Executives Say Skills Most Important
5

6. What Are The Questions?
• What is my workforce skill map?
• Where are skills grouped?
• Programs
• Projects
• Location
• Can I identify adjacent skills?
• Cypher à SQL
• Python à R
• I want to change careers, what should I learn?
6

7. Define Your Model
Information Technology Competency Model
7
Source: Employment and Training Administration US DOL

8. Core Elements of Skill Inventory Systems
8

9. Gather the Data
Governmental Approaches
9

10. ONET-SOC 2019 Taxonomy
10

11. Graph Model
11

12. Occupation Ontology: Graph View
12

13. KSAT Knowledge Graph Model
13

14. Occupation Elements
14

15. Compare Work Roles
15

16. Rank Skills by Occupation
OPM Occupation SOC Group Element Value
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skill
s']
understanding written sentences and paragraphs in work
related documents. 4.5
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skill
s']
giving full attention to what other people are saying, taking
time to understand the points being made, asking questions as
appropriate, and not interrupting at inappropriate times. 4.12
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skill
s']
communicating effectively in writing as appropriate for the
needs of the audience. 4.12
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skill
s'] talking to others to convey information effectively. 4.12
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skill
s'] using mathematics to solve problems. 4.38
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skill
s']
using logic and reasoning to identify the strengths and
weaknesses of alternative solutions, conclusions or approaches
to problems. 4.25
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skill
s']
using logic and reasoning to identify the strengths and
weaknesses of alternative solutions, conclusions or approaches
to problems. 4
GS-855 electrical engineers
17-
2071.00
['Basic_Skill
s']
understanding written sentences and paragraphs in work
related documents. 3.88
16

17. Career Change
CALL gds.graph.create.cypher(‘IT_Program_Knowledge',
'MATCH (n) WHERE (n:Occupation) OR (n:Knowledge) RETURN id(n) AS id',
'MATCH (opm:OPMSeries)-[r:IN_OPM_Series]-(occ:Occupation) WHERE opm.series IN ["GS-2210-0", "GS-0080-0", "GS-0340-0", "GS-
0343-0"] WITH occ, opm MATCH (occ)-[f:Found_In]-(s:Knowledge) WHERE f.scale = "IM" AND f.datavalue > 2.99
RETURN id(occ) AS source, id(s) AS target’
)
CALL gds.nodeSimilarity.stream('IT_Program_Knowledge')
YIELD node1, node2, similarity
RETURN gds.util.asNode(node1).title AS Occupation1, gds.util.asNode(node2).title AS Occupation2, similarity
ORDER BY Occupation1
17
Occupation1 Occupation2 similarity
management analysts online merchants 57.14%
management analysts search marketing strategists 46.15%
management analysts business intelligence analysts 46.15%
management analysts information technology project managers 43.75%
management analysts informatics nurse specialists 38.89%
management analysts geospatial information scientists and technologists 33.33%
management analysts web administrators 33.33%
management analysts sustainability specialists 33.33%
management analysts business continuity planners 31.25%
management analysts telecommunications engineering specialists 29.41%

18. Adding to Knowledge Graph
18

19. KSATs by Project
19

20. More to Come
• Recommendation Engine
• I have certain skills, what jobs are available
• I need certain skills for my project, who is available
• Expert Finder
• Develop Training Plans
• Outline Career paths
20

21. Contact Information
David Meza – david.meza-1@nasa.gov
Twitter - @davidmeza1
Linkedin - https://www.linkedin.com/in/davidmeza1/
Github – davidmeza1